Overlay Bandwidth Management: Scheduling and Active Queue Management of Overlay Flows

2020

SN COMPUT. SCI.

Self Cite

The use of online social networks, such as Facebook and Twitter, has grown at a phenomenal rate. These platforms offer services that support interactions via messaging, chatting or audio/video conferencing, and also sharing of content. Most, if not all, of these platforms use centralized computing systems; therefore, the control and management of the systems lies entirely in the hands of one provider, who must be trusted to treat the data and communication traces securely. As a zero-trust alternative, peer-to-peer (P2P) technologies promise to support end-to-end communication, uncompromising access control, anonymity and resilience against censorship and massive data leaks through misused trust. The goals of this survey are threefold. First, the survey elaborates the properties of P2P-based online social networks and defines the requirements for such (zero-trust) platforms. Second, it gives an exposition of the building blocks for P2P frameworks that allow the creation of such sophisticated and demanding applications, such as user/identity management, reliable data storage, secure communication, access control and general-purpose extensibility, which are not properly addressed in other P2P surveys. As a third point, it gives a comprehensive analysis of proposed P2P-based online social network applications, frameworks and architectures by exploring the technical details, inter-dependencies and maturity of these solutions.

Section: Uses Of Monitoring Information Monitoring Information Can Bementioning

confidence: 99%

Peer-to-Peer-Based Social Networks: A Comprehensive Survey

Masinde

2020

SN COMPUT. SCI.

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“…Although PeerfactSim.KOM consumes more memory and needs more time to finish the simulation in comparison with PeerSim and ProtoPeer, the difference is small. This overhead mainly comes from the layering in PeerfactSim.KOM that aims to support not only overlay protocols but also further higher and lower layer protocols, such as monitoring or low‐layer message prioritization . These additional layers, even if using dummies, still consume computing time and add to the memory consumption.…”

Section: Comparison With Other Simulatorsmentioning

confidence: 99%

Systematic evaluation of peer‐to‐peer systems using PeerfactSim.KOM

Feldotto

Concurrency and Computation

2015

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Summary Comparative evaluations of peer‐to‐peer protocols through simulations are a viable approach to judge the performance and costs of the individual protocols in large‐scale networks. In order to support this work, we present the peer‐to‐peer system simulator PeerfactSim.KOM, which we extended over the last years. PeerfactSim.KOM comes with an extensive layer model to support various facets and protocols of peer‐to‐peer networking. In this article, we describe PeerfactSim.KOM and show how it can be used for detailed measurements of large‐scale peer‐to‐peer networks. We enhanced PeerfactSim.KOM with a fine‐grained analyzer concept, with exhaustive automated measurements and gnuplot generators as well as a coordination control to evaluate sets of experiment setups in parallel. Thus, by configuring all experiments and protocols only once and starting the simulator, all desired measurements are performed, analyzed, evaluated, and combined, resulting in a holistic environment for the comparative evaluation of peer‐to‐peer systems. An immediate comparison of different configurations and overlays under different aspects is possible directly after the execution without any manual post‐processing. Copyright © 2015 John Wiley & Sons, Ltd.

“…The statistic gather times can even be accelerated [26]. Each node has a state and a load of O(k) with k being the tree degree.…”

Section: B Aggregation Of Network Statisticsmentioning

confidence: 99%

Continuous Gossip-Based Aggregation through Dynamic Information Aging

Rapp

2013 22nd International Conference on Computer Communication and Networks (ICCCN)

2013

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Existing solutions for gossip-based aggregation in peer-to-peer networks use epochs to calculate a global estimation from an initial static set of local values. Once the estimation converges system-wide, a new epoch is started with fresh initial values. Long epochs result in precise estimations based on old measurements and short epochs result in imprecise aggregated estimations. In contrast to this approach, we present in this paper a continuous, epoch-less approach which considers fresh local values in every round of the gossip-based aggregation. By using an approach for dynamic information aging, inaccurate values and values from left peers fade from the aggregation memory. Evaluation shows that the presented approach for continuous information aggregation in peer-to-peer systems monitors the system performance precisely, adapts to changes and is lightweight to operate.